{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/112665"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/112665","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Beagle : automated extraction and interpretation of visualizations from the web","abstract":"In this paper, we present Beagle, an automated data collection system to mine the web for SVG-based visualization images, label them with their corresponding visualization type (i.e., bar, scatter, pie, etc.), and make them available as a queryable data store. The key idea behind Beagle is a new SVG-based classification design to more effectively label visualizations rendered in a browser. Furthermore, Beagle is designed from the ground up to be extendable and modifiable in a straightforward way, to anticipate when new artifacts appear on the web, such as new JavaScript libraries, new visualization types, and better browser support for SVG. We evaluated Beagle's classification techniques on multiple collections of SVG-based visualizations extracted from the web, and found that Beagle provides a significant boost in accuracy compared to existing classification techniques, across a wide variety of visualization types.","abstract_html":"In this paper, we present Beagle, an automated data collection system to mine the web for SVG-based visualization images, label them with their corresponding visualization type (i.e., bar, scatter, pie, etc.), and make them available as a queryable data store. The key idea behind Beagle is a new SVG-based classification design to more effectively label visualizations rendered in a browser. Furthermore, Beagle is designed from the ground up to be extendable and modifiable in a straightforward way, to anticipate when new artifacts appear on the web, such as new JavaScript libraries, new visualization types, and better browser support for SVG. We evaluated Beagle's classification techniques on multiple collections of SVG-based visualizations extracted from the web, and found that Beagle provides a significant boost in accuracy compared to existing classification techniques, across a wide variety of visualization types.","abstract_has_math":false,"creators":["Duan, Peitong"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.","school":null,"contributors":[],"advisors":["Michael Stonebraker."],"committee_chairs":[],"committee_members":[],"year":2017,"date_issued":"2017","date_published":"2017","updated_at":"2026-07-22T22:21:34Z","subjects":["Electrical Engineering and Computer Science."],"languages":["eng"],"rights":["MIT theses are protected by copyright. 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They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission."]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://dspace.mit.edu/handle/1721.1/7582"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/1721.1/112665"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.","This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.","Cataloged from student-submitted student-submitted PDF version of thesis.","Includes bibliographical references (pages 71-74)."]},{"key":"dc:description.abstract","label":"Abstract","values":["In this paper, we present Beagle, an automated data collection system to mine the web for SVG-based visualization images, label them with their corresponding visualization type (i.e., bar, scatter, pie, etc.), and make them available as a queryable data store. The key idea behind Beagle is a new SVG-based classification design to more effectively label visualizations rendered in a browser. Furthermore, Beagle is designed from the ground up to be extendable and modifiable in a straightforward way, to anticipate when new artifacts appear on the web, such as new JavaScript libraries, new visualization types, and better browser support for SVG. We evaluated Beagle's classification techniques on multiple collections of SVG-based visualizations extracted from the web, and found that Beagle provides a significant boost in accuracy compared to existing classification techniques, across a wide variety of visualization types."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["M. Eng."]},{"key":"dc:title","label":"Title","values":["Beagle : automated extraction and interpretation of visualizations from the web"]}]}],"canonical_facts":{"dc:contributor.advisor":["Michael Stonebraker."],"dc:contributor.department":["Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science."],"dc:contributor.other":["Massachusetts Institute of Technology. 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The key idea behind Beagle is a new SVG-based classification design to more effectively label visualizations rendered in a browser. Furthermore, Beagle is designed from the ground up to be extendable and modifiable in a straightforward way, to anticipate when new artifacts appear on the web, such as new JavaScript libraries, new visualization types, and better browser support for SVG. We evaluated Beagle's classification techniques on multiple collections of SVG-based visualizations extracted from the web, and found that Beagle provides a significant boost in accuracy compared to existing classification techniques, across a wide variety of visualization types."],"dc:description.degree":["M. Eng."],"dc:identifier.uri":["http://hdl.handle.net/1721.1/112665"],"dc:language.iso":["eng"],"dc:publisher":["Massachusetts Institute of Technology"],"dc:rights":["MIT theses are protected by copyright. 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